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Use of Bayesian geostatistical prediction to estimate local variations in Schistosoma haematobium infection in western Africa

Firth, Sonja; Dembelé, Robert; Garba, Amadou; Touré, Seydou; Sacko, Moussa; Landoure, Aly; Bosque-Oliva, Elisa; Barnett, Adrian; Brooker, Simon; Fenwick, A; Clements, Archie


Objective: To predict the subnational spatial variation in the number of people infected with Schistosoma haematobium in Burkina Faso, Mali and the Niger prior to national control programmes. Methods: We used field survey data sets covering a contiguous area 2750 x 850 km and including 26 790 school-age children (5-14 years old) in 418 schools. The prevalence of high- and low-intensity infection and associated 95% credible intervals (CrIs) were predicted using Bayesian geostatistical models....[Show more]

CollectionsANU Research Publications
Date published: 2009
Type: Journal article
Source: Bulletin of the World Health Organization
DOI: 10.2471/BLT.08.058933


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